惯性测量装置
计算机科学
超宽带
保险丝(电气)
扩展卡尔曼滤波器
卡尔曼滤波器
实时计算
多向性
低延迟(资本市场)
带宽(计算)
计算机视觉
人工智能
工程类
电信
计算机网络
电气工程
结构工程
节点(物理)
作者
Jiaxin Li,Yingcai Bi,Kun Li,Kangli Wang,Feng Lin,Ben M. Chen
出处
期刊:Cornell University - arXiv
日期:2018-01-01
被引量:10
标识
DOI:10.48550/arxiv.1807.10913
摘要
Driven by applications like Micro Aerial Vehicles (MAVs), driver-less cars, etc, localization solution has become an active research topic in the past decade. In recent years, Ultra Wideband (UWB) emerged as a promising technology because of its impressive performance in both indoor and outdoor positioning. But algorithms relying only on UWB sensor usually result in high latency and low bandwidth, which is undesirable in some situations such as controlling a MAV. To alleviate this problem, an Extended Kalman Filter (EKF) based algorithm is proposed to fuse the Inertial Measurement Unit (IMU) and UWB, which achieved 80Hz 3D localization with significantly improved accuracy and almost no delay. To verify the effectiveness and reliability of the proposed approach, a swarm of 6 MAVs is set up to perform a light show in an indoor exhibition hall. Video and source codes are available at https://github.com/lijx10/uwb-localization
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